{"id":"https://openalex.org/W3186823848","doi":"https://doi.org/10.1109/ijcb52358.2021.9484383","title":"Leveraging Adversarial Learning for the Detection of Morphing Attacks","display_name":"Leveraging Adversarial Learning for the Detection of Morphing Attacks","publication_year":2021,"publication_date":"2021-07-20","ids":{"openalex":"https://openalex.org/W3186823848","doi":"https://doi.org/10.1109/ijcb52358.2021.9484383","mag":"3186823848"},"language":"en","primary_location":{"id":"doi:10.1109/ijcb52358.2021.9484383","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcb52358.2021.9484383","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Joint Conference on Biometrics (IJCB)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5032412535","display_name":"Zander Blasingame","orcid":"https://orcid.org/0000-0002-9508-8425"},"institutions":[{"id":"https://openalex.org/I16944753","display_name":"Clarkson University","ror":"https://ror.org/03rwgpn18","country_code":"US","type":"education","lineage":["https://openalex.org/I16944753"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Zander Blasingame","raw_affiliation_strings":["Clarkson University, Potsdam, NY, USA"],"affiliations":[{"raw_affiliation_string":"Clarkson University, Potsdam, NY, USA","institution_ids":["https://openalex.org/I16944753"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100322200","display_name":"Chen Liu","orcid":"https://orcid.org/0000-0003-1558-6836"},"institutions":[{"id":"https://openalex.org/I16944753","display_name":"Clarkson University","ror":"https://ror.org/03rwgpn18","country_code":"US","type":"education","lineage":["https://openalex.org/I16944753"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chen Liu","raw_affiliation_strings":["Clarkson University, Potsdam, NY, USA"],"affiliations":[{"raw_affiliation_string":"Clarkson University, Potsdam, NY, USA","institution_ids":["https://openalex.org/I16944753"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5032412535"],"corresponding_institution_ids":["https://openalex.org/I16944753"],"apc_list":null,"apc_paid":null,"fwci":0.9607,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.77348039,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10828","display_name":"Biometric Identification and Security","score":0.9896000027656555,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9868000149726868,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/morphing","display_name":"Morphing","score":0.9616779088973999},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.810945987701416},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.7192688584327698},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6723913550376892},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.5461987853050232},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.5289290547370911},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5018625259399414},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.4645855724811554},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.43374183773994446},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42347362637519836},{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.4133802652359009},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.40666407346725464},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.13376522064208984}],"concepts":[{"id":"https://openalex.org/C50637493","wikidata":"https://www.wikidata.org/wiki/Q1136781","display_name":"Morphing","level":2,"score":0.9616779088973999},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.810945987701416},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.7192688584327698},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6723913550376892},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.5461987853050232},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.5289290547370911},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5018625259399414},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.4645855724811554},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.43374183773994446},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42347362637519836},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.4133802652359009},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.40666407346725464},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.13376522064208984},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcb52358.2021.9484383","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcb52358.2021.9484383","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Joint Conference on Biometrics (IJCB)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1502160187","https://openalex.org/W1823734985","https://openalex.org/W1936981920","https://openalex.org/W1997011019","https://openalex.org/W2015475217","https://openalex.org/W2039051707","https://openalex.org/W2103071307","https://openalex.org/W2104513562","https://openalex.org/W2108598243","https://openalex.org/W2115252128","https://openalex.org/W2350871683","https://openalex.org/W2564992459","https://openalex.org/W2602244503","https://openalex.org/W2617529796","https://openalex.org/W2737067721","https://openalex.org/W2738882920","https://openalex.org/W2769419222","https://openalex.org/W2787608161","https://openalex.org/W2810011391","https://openalex.org/W2940860112","https://openalex.org/W2962770929","https://openalex.org/W2962793481","https://openalex.org/W2976439153","https://openalex.org/W2985068832","https://openalex.org/W2995969064","https://openalex.org/W3009760458","https://openalex.org/W3024925547","https://openalex.org/W3088392660","https://openalex.org/W3094950701","https://openalex.org/W3097243384","https://openalex.org/W3112507059","https://openalex.org/W3154569431","https://openalex.org/W4287555005","https://openalex.org/W4394512833","https://openalex.org/W6630005630","https://openalex.org/W6640316281","https://openalex.org/W6675960827","https://openalex.org/W6677618333","https://openalex.org/W6738279199","https://openalex.org/W6746311579","https://openalex.org/W6779657984","https://openalex.org/W6784683137"],"related_works":["https://openalex.org/W1574414179","https://openalex.org/W1679315481","https://openalex.org/W4362597605","https://openalex.org/W3151495635","https://openalex.org/W4385170164","https://openalex.org/W3009056573","https://openalex.org/W4236870338","https://openalex.org/W2016917053","https://openalex.org/W2922073769","https://openalex.org/W4297676672"],"abstract_inverted_index":{"An":[0],"emerging":[1],"threat":[2],"towards":[3],"face":[4,9],"recognition":[5],"systems":[6],"(FRS)":[7],"is":[8,152],"morphing":[10,42,82,189],"attack,":[11],"which":[12,60,77],"involves":[13],"the":[14,36,40,63,81,91,99,148,155,165],"combination":[15],"of":[16,39,57,147,180],"two":[17,20],"faces":[18],"from":[19],"different":[21,188],"identities":[22],"into":[23],"a":[24,125,141],"singular":[25],"image":[26,58,101],"that":[27,135],"would":[28],"trigger":[29],"an":[30],"acceptance":[31],"for":[32,128],"either":[33],"identity":[34],"within":[35],"FRS.":[37],"Many":[38],"existing":[41],"attack":[43,83],"detection":[44,178],"(MAD)":[45],"approaches":[46],"have":[47],"been":[48,71],"trained":[49,86],"and":[50,176],"evaluated":[51,186],"on":[52],"datasets":[53],"with":[54],"limited":[55],"variation":[56],"characteristics,":[59],"can":[61,78],"make":[62],"approach":[64],"prone":[65],"to":[66,113,139],"overfitting.":[67],"Additionally,":[68],"there":[69],"has":[70,106,173],"difficulty":[72],"in":[73],"developing":[74],"MAD":[75,103,118],"algorithms":[76,134],"generalize":[79],"beyond":[80],"they":[84],"were":[85],"on,":[87],"as":[88],"shown":[89],"by":[90],"most":[92],"recent":[93],"NIST":[94],"FRVT":[95],"MORPH":[96],"report.":[97],"Furthermore,":[98],"Single":[100],"based":[102,117,132,158],"(S-MAD)":[104],"problem":[105],"had":[107],"poor":[108],"performance,":[109],"especially":[110],"when":[111,185],"compared":[112],"its":[114],"counterpart,":[115],"Differential":[116],"(D-MAD).":[119],"In":[120],"this":[121],"work,":[122],"we":[123],"propose":[124],"novel":[126],"architecture":[127],"training":[129],"deep":[130],"learning":[131,138],"S-MAD":[133,150,159],"leverages":[136],"adversarial":[137],"train":[140],"more":[142],"robust":[143,177],"detector.":[144],"The":[145,170],"performance":[146,179],"proposed":[149,171],"method":[151,172],"benchmarked":[153],"against":[154,187],"state-of-the-art":[156],"VGG19":[157],"algorithm":[160],"over":[161],"36":[162],"experiments":[163],"using":[164],"ISO-IEC":[166],"30107-3":[167],"evaluation":[168],"metrics.":[169],"demonstrated":[174],"superior":[175],"less":[181],"than":[182],"5%":[183],"D-EER":[184],"attacks.":[190]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
